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    Unconditional and conditional analysis of flow and solute transport in variably saturated porous media

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    Author
    Li, Bailing
    Issue Date
    1998
    Keywords
    Hydrology.
    Agriculture, Soil Science.
    Environmental Sciences.
    Advisor
    Yeh, T.-C. Jim
    
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    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    A numerical first order approach is proposed to conduct stochastic analyses of head and concentration under variably saturated conditions. The approach is based on a first-order Taylor series expansion and an adjoint state method. To implement the approach in different flow and transport regimes, numerical models are adopted to evaluate sensitivities of head and concentration with respect to hydrological parameters. This provides the possibility of conducting stochastic analyses of flow and transport problems with any kind of boundary and initial conditions. As a result, limitations of analytical approaches such as the spectral/perturbation approach can be avoided. In addition, the use of adjoint state method also alleviates the computational burden encountered in Monte Carlo simulation by allowing us to evaluate the sensitivities of head and concentration only at interesting/measurement locations. Several numerical simulations are performed to examine the sensitivities and moments of head and concentration under different flow conditions. The results show that the existence of water tables in the simulation domain can have a significant impact on the moment calculation of head and concentration. The calculated statistical moments are used to estimate log-conductivity by cokriging. The conditioning effect of head, concentration, and arrival time in estimating log-conductivity is investigated under different flow conditions. The results show steady state head is the best secondary information compared to solute concentration and arrival time in estimating conductivity by providing stable and consistent results. Estimates can be error prone when concentration measurements are used to estimate LnKs because of the nonlinear relationship between concentration and LnKs and the large variability in the simulated solute plumes. A sequential estimating technique is shown to be able to overcome some of these inadequacies of using concentration measurements. Arrival time, requiring a large amount of CPU time, does not show any advantage over concentration and head in estimating conductivity.
    Type
    text
    Dissertation-Reproduction (electronic)
    Degree Name
    Ph.D.
    Degree Level
    doctoral
    Degree Program
    Graduate College
    Hydrology and Water Resources
    Degree Grantor
    University of Arizona
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